By Chad Brisoe, Ph. D.
Imagine a laboratory without crowded shelves or cluttered stacks of bound notebooks and study binders. With the electronic laboratory notebook (ELN), that vision is becoming a reality. ELNs add a new level of convenience to data capturing, sharing, and study collaboration. Although many organizations are embracing the use of ELNs in their labs, there are some who are hesitant to make the switch. Those who have adopted the ELN system, however, have noticed improved efficiency and improved quality of data, among other benefits.
Many scientists find themselves double checking or triple checking data, putting forth unnecessary labor to ensure data is recorded properly and errors are avoided. ELNs help streamline the entire data processing workflow. Quality control is integrated in the process, and common features include embedded Excel spreadsheets to ensure validated data, email integration to help approve data, tracking and trending of key data in grid views and metric plots, and global searching of data from other laboratories.
ELNs appear to have a clear advantage over traditional documentation methods, yet many laboratories find it challenging to get users to buy in to the ELN system. Often, scientists are averse to change and prefer to work at their own pace with their own systems. However, there are some scientists who embrace the technology, which leads us to the first way ELNs are typically implemented — through grassroots enthusiasm.
The lab team usually finds the need for an ELN system, which they then propose to senior management. This is advantageous because it’s driven by people who really want or need the system; however, the challenge lies in convincing senior management to invest in the product. The other way ELN systems are adopted is through a top-down approach. This is when senior management identifies the need and asks for a project investigation or proposal. Benefits of this include senior level support and good funding/resourcing of the project, but the disadvantage is having to adapt to a new system that the user may be unfamiliar with.
Features Designed For Bioanalytical Labs
In recent years, ELN providers have developed a better understanding of the bioanalytical market. Distinct features for bioanalytical labs include flexible forms/templates, pick lists for key terms to help produce cleaner data, and validation rules to avoid inaccuracy. Some features vary between systems, with each having their own advantages and disadvantages, depending on what your lab is looking for.
There are various companies who distribute ELN systems for the bioanalytical market. Some notable systems with key features include:
Waters SDMS Vision Publisher — format allows integration with Waters Empower and NuGenesis
Symyx Notebook by Accelrys — allows cross-study browsing with Watson integration
IDBS E-WorkBook Suite — cross-disciplinary ELN with templates and workflows designed for bioanalysis
Laboratory Data Solutions Labnotes — contains flexible forms and out-of-the-box implementation for bioanalysis
ArtusLabs Ensemble Electronic Lab Notebook (E2LN) — deep search capability and option to have vendor-hosted ELN
Agilent ELN — form-based ELN suite for corporate integration with other Agilent systems
Velquest SmartLab — highly structured, form-based system, GMP level compliance
CambridgeSoft E-Notebook — performs unique calculations with your Watson data, recognized name
Although the ELN has yet to become the universal standard, it appears to be just a matter of time before it does. ELNs significantly streamline and simplify the collection and use of data, and today each lab can find one that suits their needs. In a digital age, the transition to the ELN is a natural step forward.
Chad Briscoe, Ph.D., is currently the senior director of bioanalysis at PRA International, where he is leading their new bioanalytical laboratory in Kansas City. He has become well-known in the bioanalytical community as an expert in the use of advanced LC/MS/MS technology applied to high-throughput analysis, system suitability in high-throughput LC/MS/MS, and bioanytical software validation.